Abstract
We compare two common methods for detecting effective or functional connectivity: thresholding correlations and singular value decomposition (SVD). We find that thresholding correlations is better at detecting focal regions of correlated voxels, whereas SVD is better at detecting extensive regions of correlated voxels. We apply these results to resting state networks in an fMRI data set, and to look for anatomical connectivity in cortical thickness.